AIMC Topic: Machine Learning

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Investigating Ligand-Mediated Conformational Dynamics of Pre-miR21: A Machine-Learning-Aided Enhanced Sampling Study.

Journal of chemical information and modeling
MicroRNAs (miRs) are short, noncoding RNA strands that regulate the activity of mRNAs by affecting the repression of protein translation, and their dysregulation has been implicated in several pathologies. miR21 in particular has been implicated in t...

Machine learning-based predictive model for post-stroke dementia.

BMC medical informatics and decision making
BACKGROUND: Post-stroke dementia (PSD), a common complication, diminishes rehabilitation efficacy and affects disease prognosis in stroke patients. Many factors may be related to PSD, including demographic, comorbidities, and examination characterist...

Explainable machine learning model for predicting the risk of significant liver fibrosis in patients with diabetic retinopathy.

BMC medical informatics and decision making
BACKGROUND: Diabetic retinopathy (DR), a prevalent complication in patients with type 2 diabetes, has attracted increasing attention. Recent studies have explored a plausible association between retinopathy and significant liver fibrosis. The aim of ...

Analyzing immune cell infiltrates in skeletal muscle of infantile-onset Pompe disease using bioinformatics and machine learning.

Scientific reports
Pompe disease, a severe lysosomal storage disorder, is marked by heart problems, muscle weakness, and respiratory difficulties. This study aimed to identify novel markers for infantile-onset Pompe disease by analyzing key genes and immune cells infil...

Gender-specific aspects of socialisation and risk of cardiovascular disease among community-dwelling older adults: a prospective cohort study using machine learning algorithms and a conventional method.

Journal of epidemiology and community health
BACKGROUND: Gender influences cardiovascular disease (CVD) through norms, social relations, roles and behaviours. This study identified gender-specific aspects of socialisation associated with CVD.

Detection of breast cancer using machine learning on time-series diffuse optical transillumination data.

Journal of biomedical optics
SIGNIFICANCE: Optical mammography as a promising tool for cancer diagnosis has largely fallen behind expectations. Modern machine learning (ML) methods offer ways to improve cancer detection in diffuse optical transmission data.

Improving drug-target interaction prediction through dual-modality fusion with InteractNet.

Journal of bioinformatics and computational biology
In the drug discovery process, accurate prediction of drug-target interactions is crucial to accelerate the development of new drugs. However, existing methods still face many challenges in dealing with complex biomolecular interactions. To this end,...

Enhancing type 2 diabetes mellitus prediction by integrating metabolomics and tree-based boosting approaches.

Frontiers in endocrinology
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a global health problem characterized by insulin resistance and hyperglycemia. Early detection and accurate prediction of T2DM is crucial for effective management and prevention. This study explores the ...

Explainable machine learning for early prediction of sepsis in traumatic brain injury: A discovery and validation study.

PloS one
BACKGROUND: People with traumatic brain injury (TBI) are at high risk for infection and sepsis. The aim of the study was to develop and validate an explainable machine learning(ML) model based on clinical features for early prediction of the risk of ...

Exploring machine learning algorithms in sickle cell disease patient data: A systematic review.

PloS one
This systematic review explores the application of machine learning (ML) algorithms in sickle cell disease (SCD), focusing on diagnosis and several clinical characteristics, such as early detection of organ failure, identification of drug dosage, and...